Fingerprint recognition method and electronic interactive apparatus thereof

ABSTRACT

A fingerprint recognition method is provided. The method includes obtaining a plurality of fingerprint images by sensing a finger of a user, respectively calculating geometric center points corresponding to the fingerprint images, and calculating positions and offsets of the fingerprint images according to the geometric center points. The method also includes filling signals in the fingerprint images into a part of pixels in a pixel array according to the positions and the offsets of the fingerprint images, and obtaining signals of other pixels in the pixel array by inputting the signals filled in the part of pixels in the pixel array into an artificial intelligence engine. The method further includes generating a candidate fingerprint image and recognizing a user based on the candidate fingerprint image.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the priority benefit of Taiwan application no.109116491, filed on May 19, 2020. The entirety of the above-mentionedpatent application is hereby incorporated by reference herein.

TECHNICAL FIELD

The disclosure relates to a fingerprint recognition method and anelectronic interactive apparatus thereof.

BACKGROUND

With the rapid development of touch display and recognition technology,quite a few applications have been derived. For example, after anoperator of a touch display is recognized, personalized interface andinformation may be provided on a touch screen.

At present, a touch display equipped with a fingerprint capturing devicehas been developed, which can recognize a user using the touch screenand provide a personalized interaction. In general, to be able torecognize fingerprints, a captured image needs to have high resolutionof, for example, at least 500 dpi to 1200 dpi. However, in certainapplications, high resolution fingerprint images cannot be captured. Forexample, a transparent display cannot be configured with sensors withsuch a high density in consideration of a transmission rate. Therefore,how to recognize the user based on the fingerprint image and provide thecorresponding interaction and information without capturing highresolution images is the goal of those skilled in the art.

SUMMARY

According to an exemplary embodiment of the disclosure, a fingerprintrecognition method is provided. The method includes detecting a touchsignal corresponding to a user on a touch display, and sensing a fingerof the user to obtain a plurality of fingerprint images through afingerprint sensor disposed on the touch display, wherein thefingerprint sensor has a plurality of sensing units and the finger ofthe user moves on the sensing units. The method further includesrespectively calculating geometric center points corresponding to thefingerprint images, and calculating positions and offsets of thefingerprint images according to the geometric center points. The methodalso includes filling signals in the fingerprint images into a part ofpixels in a pixel array according to the positions and the offsets ofthe fingerprint images, and obtaining signals of other pixels in thepixel array by inputting the signals filled in the part of pixels in thepixel array into an artificial intelligence engine. The method furtherincludes generating a candidate fingerprint image and recognizing a userbased on the candidate fingerprint image.

According to an exemplary embodiment of the disclosure, an electronicinteractive apparatus is provided and includes a processor, a touchdisplay, a fingerprint sensor and a storage device. The touch display iscoupled to the processor, and configured to detect a touch signalcorresponding to a user. The fingerprint sensor is coupled to theprocessor, and configured to sense a finger of the user to obtain aplurality of fingerprint images, wherein the fingerprint sensor has aplurality of sensing units and the finger of the user moves on thesensing units. The storage device is coupled to the processor. Here, thefingerprint sensor respectively calculates geometric center pointscorresponding to the fingerprint images, and calculates positions andoffsets of the fingerprint images according to the geometric centerpoints corresponding to the fingerprint images. Further, the fingerprintsensor fills signals in the fingerprint images into a part of pixels ina pixel array according to the positions and the offsets of thefingerprint images, and obtains signals of other pixels in the pixelarray by inputting the signals filled in the part of pixels in the pixelarray into an artificial intelligence engine. Furthermore, thefingerprint sensor generates a candidate fingerprint image according tothe pixel array. The processor recognizes the user according to thecandidate fingerprint image.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram for sensing fingerprints illustratedaccording to the conventional art.

FIG. 2 is a schematic diagram for sensing fingerprints illustratedaccording to an exemplary embodiment of the disclosure.

FIG. 3 is a schematic diagram of an interactive apparatus illustratedaccording to an exemplary embodiment of the disclosure.

FIG. 4 is a block diagram of an interactive apparatus illustratedaccording to an exemplary embodiment of the disclosure.

FIG. 5 is a schematic diagram for generating a high resolutionfingerprint image illustrated according to an exemplary embodiment ofthe disclosure.

FIGS. 6A, 6B, 6C and 6D are schematic diagrams for calculating geometriccenter points illustrated according to an exemplary embodiment of thedisclosure.

FIG. 7 is a schematic diagram for calculating offsets illustratedaccording to an exemplary embodiment of the disclosure.

FIG. 8 is a schematic diagram for filling pixels illustrated accordingto an exemplary embodiment of the disclosure.

FIG. 9 is a flowchart of a fingerprint recognition method illustratedaccording to an exemplary embodiment of the disclosure.

FIG. 10 is a flowchart of detailed steps for determining whether a pixelsignal quantity of a pixel array is sufficient in FIG. 9 illustratedaccording to an exemplary embodiment of the disclosure.

FIG. 11 is a flowchart for performing a fingerprint recognition torecognize a corresponding user illustrated according to an exemplaryembodiment of the disclosure.

FIG. 12 is a flowchart of a fingerprint recognition method illustratedaccording to another exemplary embodiment of the disclosure.

DETAILED DESCRIPTION

FIG. 1 is a schematic diagram for sensing fingerprints illustratedaccording to the conventional art, and FIG. 2 is a schematic diagram forsensing fingerprints illustrated according to an exemplary embodiment ofthe disclosure.

Referring to FIG. 1 and FIG. 2, in an example where a user recognizingfunction is implemented on devices such as a tablet computer, aninteractive TV wall or the like, sensors are disposed under a displayscreen to sense a fingerprint of a user. As described above, in order torecognize the fingerprint, a captured image needs to have sufficientresolution. An object to be measured may be completely covered by usinga detection range of the sensors having sufficient density (e.g., asshown in FIG. 1). However, in an application (e.g., a transparentdisplay) of an exemplary embodiment of the disclosure, when the sensorsare configured with a lower density in consideration of a transmissionrate, a local area may be detected (as shown in FIG. 2).

FIG. 3 is a schematic diagram of an interactive apparatus illustratedaccording to an exemplary embodiment of the disclosure, and FIG. 4 is ablock diagram of an interactive apparatus illustrated according to anexemplary embodiment of the disclosure.

Referring to FIG. 3 and FIG. 4, an electronic interactive apparatus 300includes a processor 302, a touch display 304, a fingerprint sensor 306and a storage device 308. The touch display 304, the fingerprint sensor306 and the storage device 308 are coupled to the processor 302. Theelectronic interactive apparatus 300 is, for example, a mobile device, apersonal digital assistant (PDA), a notebook computer, a tabletcomputer, a general desktop computer, an interactive display board, aninteractive TV wall, an interactive transparent display board, or otherelectronic device, which is not limited herein.

The processor 302 may be, for example, a processor for general purposes,a processor for special purposes, a conventional processor, a datasignal processor, a plurality of microprocessors, one or moremicroprocessors, controllers, microcontrollers and Application SpecificIntegrated Circuit (ASIC) which are combined to a core of the digitalsignal processor, a Field Programmable Gate Array (FPGA), any otherintegrated circuits, a state machine, a processor based on Advanced RISCMachine (ARM) and similar products.

The touch display 304 may be used to receive a touch signal and displaya corresponding interface according to instructions from the processor302. For example, the touch display 304 may be an LED display, a liquidcrystal display, a transparent display, a flexible display or othersuitable display types provided with touch control elements.

The fingerprint sensor 306 includes a plurality of sensing units 310 anda fingerprint image processing unit 312. The sensing units 310 may bearranged under the touch display 304 in an array manner (as shown inFIG. 2) to detect a fingerprint of the user. The fingerprint imageprocessor unit 312 is coupled to the sensing units 310 and configured togenerate a fingerprint image of the user.

The storage device 308 may be, for example, any fixed or movable deviceincluding a RAM (Random Access Memory), a ROM (Read-Only Memory), aflash memory, a hard drive or other similar devices or a combination ofthe above-mentioned devices. In this exemplary embodiment, the storagedevice 308 is configured to store a fingerprint image registered by theuser, which may be used as a reference for recognizing the user insubsequent processes. In another exemplary embodiment, the storagedevice 308 is further stored with programs such as a computing module, acontrol module or the like, which may be operated by the processor 302to perform a fingerprint recognition and execute a correspondinginteractive interface.

In an exemplary embodiment of the disclosure, when the touch signal isdetected, the electronic interactive apparatus 300 may obtain aplurality of low resolution fingerprint images, and generate a highresolution fingerprint image based on the low resolution fingerprintimages. In addition, the electronic interactive apparatus 300 mayrecognize the user operating the electronic interactive apparatus 300according to the high resolution fingerprint image to correspondinglyoutput an interactive interface.

FIG. 5 is a schematic diagram for generating a high resolutionfingerprint image illustrated according to an exemplary embodiment ofthe disclosure.

Referring to FIG. 5, when the finger of the user moves on the touchdisplay 304 (S501), the touch display 304 may receive the touch signal,and the processor 302 may instruct the fingerprint sensor 306 to sense afingerprint signal to obtain a plurality of low resolution fingerprintimages (S502).

Next, the fingerprint image processing unit 312 may respectivelycalculate geometric center points of the low resolution fingerprintimages. For example, after signals are received form the sensing units310, the fingerprint image processing unit 312 determines the geometriccenter points of the fingerprint images according to all pixels havingsignals (as shown in FIG. 6A). However, the disclosure is not limited inthis regard. After signals are received form the sensing units 310, thefingerprint image processing unit 312 may also determine the geometriccenter points of the fingerprint images according to a contour of allpixels having signals (as shown in FIG. 6A). For example, the contour ofthe pixels may be a straight line parallel or perpendicular to a pixelarrangement direction (as shown in FIG. 6B), or a diagonal line with a45 degree angle to the pixel arrangement direction (as shown in FIG.6C). Alternatively, the contour of the pixels may be multi-layered (asshown in FIG. 6D).

After the geometric center points of the low resolution fingerprintimages are obtained, the fingerprint image processing unit 312 maycalculate a position of each of the low resolution fingerprint imagesand an offset thereof from the first low resolution fingerprint imageaccording to these geometric center points. For example, it is assumedthat, according to the geometric center point, the offset from the firstlow-resolution fingerprint image is calculated as d and horizontal andvertical distances between the sensing units 310 are px and py,respectively. Accordingly, a horizontal offset BiasX and a verticaloffset BiasY may be expressed as follows:Biasx=dx−n*pxBiasy=dy−m*py

-   -   wherein m and n are integers, 0≤Biasx<px, and 0≤Biasy<py (as        shown in FIG. 7).

Then, the fingerprint image processing unit 312 fills signals in the lowresolution fingerprint images into one high pixel array according to thepositions and the offsets of the low resolution fingerprint images(S503). The fingerprint image processing unit 312 uses other lowresolution signals (as shown in the left of FIG. 8) to perform a signalfilling (as shown in the middle of FIG. 8) to form a high resolutionsignal (as shown in the right of FIG. 8). In particular, in an exemplaryembodiment, after the signals of a part of pixels in the high pixelarray are obtained from the low resolution fingerprint image, thefingerprint image processing unit 312 inputs the obtained signals of thepixels into an artificial intelligence engine to generate signals ofother pixels in the high pixel array (S504). For example, in thisexemplary embodiment, the artificial intelligence engine may beimplemented by using an enhanced deep super resolution architecture, asuper resolution convolutional neural network or other suitableartificial intelligence engines. Lastly, the fingerprint imageprocessing unit 312 outputs the high resolution fingerprint imageaccording to the signals in the generated high pixel array (S505).

In an exemplary embodiment, during the process of signal filling, thefingerprint image processing unit 312 may continuously determine whethera filled signal quantity is sufficient for the artificial intelligenceengine to obtain a new and different image. If the filled signalquantity is insufficient, the fingerprint image processing unit 312obtains the fingerprint images from the sensing units 310 again.

For example, the fingerprint image processing unit 312 may calculate andobtain a fitting curve according to the geometric center points of theobtained low resolution fingerprint images, and calculate a length L1 ofthe fitting curve, In this exemplary embodiment, the obtained fittingcurve may pass through to the geometric center point of the last lowresolution fingerprint image, and uses the geometric center point of thelast low resolution fingerprint image as an end point. However, thedisclosure is not limited in this regard. It is also possible that thefitting curve does not pass through to the geometric center point of thelast low resolution fingerprint image, and instead, the finger imageprocessing unit 312 may select a point on the fitting curve closest tothe geometric center point of the last low resolution fingerprint imageas the end point. Furthermore, the fingerprint image processing unit 312may also select a point on the fitting curve that is away from thegeometric center point of the last low resolution fingerprint image in avertical line direction or a horizontal line direction as the end point.Similarly, when the fitting curve passes through the geometric centerpoint of the first low resolution fingerprint image, the geometriccenter point of the first low resolution fingerprint image may be usedas a start point of the fitting curve; if the fitting curve does notpass through the geometric center point of the first low resolutionfingerprint image, the fingerprint image processing unit 312 may selecta point on the fitting curve closest to the geometric center point ofthe first low resolution fingerprint image as the start point of thefitting curve. Furthermore, the fingerprint image processing unit 312may also select a point on the fitting curve that is away from thegeometric center point of the first low resolution fingerprint image inthe vertical line direction or the horizontal line direction as the endpoint.

Further, the fingerprint image processing unit 312 may calculate andobtain an extended fitting curve from the end point of the fitting curveto an edge of the fingerprint sensor 306, and calculate a length L2 ofthe extended fitting curve.

When the length L1 of the fitting curve is less than the length L2 ofthe extended fitting curve, the fingerprint image processing unit 312may determine that the filled signal quantity is insufficient. When thelength L1 of the fitting curve is not less than the length L2 of theextended fitting curve, according to the length L2 of the extendedfitting curve, the fingerprint image processing unit 312 may searchbackward from the end point of the fitting curve along the fitting curveby a length L2R equal to the extended fitting curve, and the fingerprintimage processing unit 312 may determine that the filled signal quantityis insufficient when a point of a new and different image is found inthat way.

For the convenience of explanation, it is simplified here that thelength L2 is equal to the length L2R. In fact, at each stage, aprobability of obtaining a different image is not the same, and theprobability becomes lower in later stages. For example, in a sensingarray with a resolution of 170 dpi, to perform a 3×3 image restoration,a total of nine different images need to be obtained. If two differentimages are already obtained, the probability that the next image isdifferent from the previous two images is 78% (=(9/2)/9). If sevendifferent images are already obtained, the probability of the next imageis different from the previous seven images is 22% ((9-7)/9). In otherwords, as the probability of obtaining an (N+1)th different image islower than the probability of obtaining an Nth different image, thelength L2R is estimated to be smaller than the length L2. Therefore,when the resolution of the sensing array is designed to be R dpi, theobtained low resolution images need to be restored to R₀ dpi. On thatbasis, if N different images are already obtained, a ratio relationshipof the length L2 and the length L2R is as follows:

${L2R} = {\frac{{R_{0} \times R_{0}} - {R \times R \times \left( {N - 1} \right)}}{{R_{0} \times R_{0}} - {R \times R \times N}} \times L2}$

Among them, L2<L2R≤2 (L2), and when R₀ is 508, L2R/L2 may refer to thefollowing table:

Resolution Resolution Resolution Resolution N 254 dpi N 170 dpi N 127dpi N 101 dpi : : 2 1.14 9 1.14 18 1.14 : : 3 1.16 10 1.16 19 1.16 : : 41.2 11 1.2 20 1.2 : : 5 1.25 12 1.25 21 1.25 1 1.33 6 1.33 13 1.33 221.33 2 1.5 7 1.5 14 1.5 23 1.5 3 2 8 2 15 2 24 2

It should be understood that the above method for determining whetherthe filled signal quantity is insufficient is only an exemplaryembodiment, and the disclosure is not limited thereto.

In this exemplary embodiment, a trajectory of the finger of the usermoving on the touch display 304 may be a closed line segment or anunclosed line segment such as circle, ellipse, square, polygon, line,arc, parabola, polygon, etc., which are not particularly limited by thedisclosure. It should be that be noted that, the finger of the userneeds to move on the touch display 304 by a certain length so that thefingerprint image processing unit 312 can receive sufficient signalsfrom the sensing unit 310 to facilitate output of the high resolutionfingerprint image. In general, a finger movement speed is, for example,11.3 cm per second. If an imaging frequency is 30 Hz, the fingermovement length needs to meet the following formula: Length(cm)≥((2*508/dpi)²)/f, wherein dpi is a density of the sensing units andf is a frame rate. The finger movement length needs be greater than 22mm if a 2×2 pixel array is used for restoration, and needs be greaterthan 68 mm if a 3×3 pixel array is used for restoration.

In this exemplary embodiment, the fingerprint image processing unit 312calculates predicted pixel signals after the finger of the user stopsmoving. In addition, in another exemplary embodiment, the fingerprintimage processing unit 312 may also make multiple predictions based onthe received signals while the finger of the user is moving. In thisway, as more signals are received when the finger movement length of theuser becomes longer, a prediction precision may be higher.

In this exemplary embodiment, the processor 302 may recognize the useroperating the electronic interactive apparatus 300 according to the highresolution fingerprint image recognized by the fingerprint imageprocessing unit 312 and the fingerprint image recorded by the storagedevice 308. For example, when no fingerprint image is recorded in thestorage device 308, the high resolution fingerprint image recognized bythe fingerprint image processing unit 312 is then recorded in thestorage device 308. Later, when the fingerprint image sensed by thefingerprint image processing unit 312 is identical to the fingerprintimage recorded in the storage device 308, the processor 302 maysuccessfully recognize the user operating the electronic interactiveapparatus 300 and provide a corresponding processing mechanism. Further,when no other touch signal of the same user is received for a period oftime, the processor 302 deletes the fingerprint image of that user fromthe storage device 308.

For example, in an exemplary embodiment where the electronic interactiveapparatus 300 can receive one user operation at the same time, when thetouch display 304 receives the touch signal, the processor 302 mayrecord the high resolution fingerprint image generated by thefingerprint image processing unit 312 into the storage device 308.Later, when the touch display 304 receives another touch signal, theprocessor 302 may compare a high resolution fingerprint image newlygenerated by the fingerprint image processing unit 312 with thefingerprint image in the storage device 308. If the newly generated highresolution fingerprint image is different from the fingerprint image inthe storage device 308, the processor 302 stops processing that touchsignal. Based on this, the processor 302 deletes the fingerprint imageof that user from the storage device 308 when no other touch signal ofthe same user is received for a period of time. Accordingly, anotheruser may register a fingerprint image to operate the electronicinteractive apparatus 300.

FIG. 9 is a flowchart of a fingerprint recognition method illustratedaccording to an exemplary embodiment of the disclosure.

Referring to FIG. 9, in step S901, the touch display 304 detects a touchsignal.

In step S903, the fingerprint sensor 306 (or the sensing units 310) maysense signals corresponding to a fingerprint of a user to obtainfingerprint images (e.g., first fingerprint images).

In step S905, the fingerprint sensor 306 (or the fingerprint imageprocessing unit 312) may calculate geometric center points of theobtained fingerprint images and accordingly calculate positions andoffsets of the calculated fingerprint images.

In step S907, the fingerprint sensor 306 (or the fingerprint imageprocessing unit 312) may fill signals in the fingerprint images intocorresponding positions of a high pixel array according to the positionsand the offsets of the fingerprint images.

In step S909, the fingerprint sensor 306 (or the fingerprint imageprocessing unit 312) may determine whether a pixel signal quantity ofthe high pixel array is sufficient.

If the pixel signal quantity of the high pixel array is insufficient,step S903 is executed to continue obtaining the fingerprint images.

If the pixel signal quantity of the high pixel array is sufficient, instep S911, the fingerprint sensor 306 inputs obtained pixel signals inthe high pixel array into an artificial intelligence engine to generatesignals of other pixels in the high pixel array.

Next, in step S913, the fingerprint sensor 306 outputs a candidatefingerprint image of high resolution according to the signals of thehigh pixel array.

Then, in step S915, the processor 302 performs a fingerprint recognitionto recognize a corresponding user according to the candidate fingerprintimage. Here, the fingerprint recognition includes procedures such ascalculating a fingerprint orientation, performing an image binarization,performing a line thinning, extracting features and performingcomparison.

FIG. 10 is a flowchart of detailed steps for determining whether a pixelsignal quantity of a pixel array is sufficient in FIG. 9 illustratedaccording to an exemplary embodiment of the disclosure.

Referring to FIG. 10, in step S917, the fingerprint sensor 306 (or thefingerprint image processing unit 312) calculates and obtains a fittingcurve according to the geometric center points of the obtainedfingerprint images, and calculates a length of the fitting curve.

In step S919, the fingerprint sensor 306 (or the fingerprint imageprocessing unit 312) calculates and obtains an extended fitting curveextended from an end point of the fitting curve to an edge of thefingerprint sensor 306 (or the fingerprint image processing unit 312),and calculates a length of the extended fitting curve.

In step S921, the fingerprint sensor 306 (or the fingerprint imageprocessing unit 312) may determine whether the length of the fittingcurve is less than the length of the extended fitting curve.

If the length of the fitting curve is less than the length of theextended fitting curve, the fingerprint sensor 306 (or the fingerprintimage processing unit 312) may determine that the filled signal quantityis insufficient.

If the length of the fitting curve is not less than the length of theextended fitting curve, in step S923, the fingerprint sensor 306 (or thefingerprint image processing unit 312) determines whether a new pixelpoint is present by searching backward from the end point of the fittingcurve along the fitting curve according to the length of the extendedfitting curve.

If the new pixel point is present, the fingerprint sensor 306 (or thefingerprint image processing unit 312) may determine that the filledsignal quantity is insufficient.

If the new pixel point is absent, the fingerprint sensor 306 (or thefingerprint image processing unit 312) may determine that the filledsignal quantity is sufficient.

FIG. 11 is a flowchart for performing a fingerprint recognition torecognize a corresponding user illustrated according to an exemplaryembodiment of the disclosure.

Referring to FIG. 11, in step S1001, the processor 302 may determinewhether a database in the storage device 308 is stored with afingerprint record.

If the database is not stored with the fingerprint record, in stepS1003, the processor 302 may store the recognized fingerprint image anda recognized timestamp in the database. Subsequently, the processor 302may process new fingerprint images (e.g., second fingerprint images) asdescribed above.

If the database is stored with the fingerprint record, in step S1005,the processor 302 may determine whether the candidate fingerprint imageis identical to the fingerprint record stored in the database.

If the candidate fingerprint image is identical to the fingerprintrecord stored in the database, in step S1007, the processor 302 mayoutput a corresponding interactive interface and update the recognizedtimestamp stored by the database.

If the candidate fingerprint image is not identical to the fingerprintrecord stored in the database, in step S1009, the processor 302 may stopto respond to the touch signal.

In another exemplary embodiment, the sensing units 310 may be disposedon a once-stretchable substrate. The once-stretchable substrate may bemade by stretchable or shrinkable materials (e.g., Ethylene VinylAcetate (EVA), Polyvinyl Chloride (PVC), Polyethylene (PE),Polytetrafluoroethylene (PTFE), Polyvinylidene Difluoride (PVDF),Ethylene Propylene Diene Monomer rubber (EPDM), etc). In the exemplaryembodiment in which the sensing units 310 are disposed on aonce-stretchable substrate, the electronic interactive apparatus 300 mayfurther include a strain detector (not shown) coupled to the processor302 to measure the strain amount of the once-stretchable substrate. And,the processor 302 obtain distances between the sensing units 310according to the strain amount of the once-stretchable substrate anddetermines whether a new pixel point (i.e., deformed pixel) is needed tocomplement after the once-stretchable substrate is stretched. Forexample, when the stretch rate is 20%, a new pixel point is added everyfive pixel points. When the stretch rate is 25%, a new pixel point isadded every four pixel points. When the stretch rate is 34%, a new pixelpoint is added every tree pixel points. Herein, the stretch rate is lessthan 50%. In addition, when the fingerprint sensor 306 inputs theobtained signals in the high pixel array into the artificialintelligence engine, a signal of the deformed pixel may be calculated.

In the exemplary embodiment, for example, the once-stretchable substratemay be transparent or non-transparent. The strain detector may be acommercially available metal foil strain gauge, or made of poly-silicon,or made of Single-Walled Carbon Nanotube (SWCNT). Additionally, thedistances between the sensing units 310 may be converted into aretrievable voltage signal by a Wheatstone bridge or Quarter bridge.

FIG. 12 is a flowchart of a fingerprint recognition method illustratedaccording to another exemplary embodiment of the disclosure.

Referring to FIG. 12, in step S1201, the strain detector measures astrain amount of the once-stretchable substrate.

In step S1203, the processor 302 calculates a stretch rate near thestrain detector.

In step S1205, the process 302 estimates a stretch of each place on theonce-stretchable substrate.

In step S1207, the processor 302 estimates distances between theplurality of sensing units, and calculates a position of at least onedeformed pixel needed to be complemented with a signal in the pixelarray. After that, the steps S901˜S915 are performed to sense touchsignals and execute the fingerprint recognition to recognize acorresponding user.

The fingerprint recognition method and the apparatus thereof accordingto the exemplary embodiments of the disclosure can use the lowresolution fingerprint images and the artificial intelligence engine togenerate the high resolution fingerprint image. As a result, theinteractive device equipped with low density fingerprint sensing unitscan use the high resolution fingerprint image to recognize the user andaccurately provide the corresponding interactive content.

Although the disclosure has been described with reference to the aboveembodiments, it will be apparent to one of ordinary skill in the artthat modifications to the described embodiments may be made withoutdeparting from the spirit of the disclosure. Accordingly, the scope ofthe disclosure will be defined by the attached claims and not by theabove detailed descriptions.

The invention claimed is:
 1. A fingerprint recognition method,comprising: detecting a touch signal corresponding to a user on a touchdisplay; sensing a finger of the user to obtain a plurality offingerprint images through a fingerprint sensor disposed on the touchdisplay, wherein the fingerprint sensor has a plurality of sensing unitsand the finger of the user moves on the sensing units; respectivelycalculating geometric center points corresponding to the fingerprintimages; calculating positions and offsets of the fingerprint imagesaccording to the geometric center points corresponding to thefingerprint images; filling signals in the fingerprint images into apart of pixels in a pixel array according to the positions and theoffsets of the fingerprint images; determining whether a signal quantityof the pixel array is sufficient; if the signal quantity of the pixelarray is sufficient, obtaining signals of other pixels in the pixelarray by inputting the signals filled in the part of pixels in the pixelarray into an artificial intelligence engine; generating a candidatefingerprint image according to the pixel array; and recognizing the useraccording to the candidate fingerprint image.
 2. The fingerprintrecognition method of claim 1, wherein a trajectory of the finger of theuser moving on the sensing units is a closed line segment or an unclosedline segment.
 3. The fingerprint recognition method of claim 1, whereinthe step of respectively calculating the geometric center pointscorresponding to the fingerprint images comprises: recognizing pixelpoints having the signals in each of the fingerprint images; andcalculating the geometric center points of the fingerprint imagesaccording to the pixel points having the signals in each of thefingerprint images.
 4. The fingerprint recognition method of claim 1,wherein the step of respectively calculating the geometric center pointscorresponding to the fingerprint images comprises: recognizing pixelpoints having the signals in each of the fingerprint images; andcalculating the geometric center points of the fingerprint imagesaccording to a contour of the pixel points having the signals in each ofthe fingerprint images.
 5. The fingerprint recognition method of claim1, further comprising: storing the candidate fingerprint image and atimestamp corresponding to the candidate fingerprint image in adatabase.
 6. The fingerprint recognition method of claim 5, furthercomprising: detecting another touch signal on the touch display; sensinga plurality of second fingerprint images through the fingerprint sensor;respectively calculating geometric center points corresponding to thesecond fingerprint images; calculating positions and offsets of thesecond fingerprint images according to the geometric center pointscorresponding to the second fingerprint images; filling signals in thesecond fingerprint images into a part of pixels in a second pixel arrayaccording to the positions and the offsets of the second fingerprintimages; obtaining signals of other pixels in the second pixel array byinputting the signals filled in the part of pixels in the second pixelarray into the artificial intelligence engine; generating a secondcandidate fingerprint image according to the second pixel array;comparing whether the second candidate fingerprint image is identical tothe candidate fingerprint image stored by the database; and if thesecond candidate fingerprint image is not identical to the candidatefingerprint image, stopping to respond to the another touch signal. 7.The fingerprint recognition method of claim 6, further comprising: whenno other touch signal corresponding to the user is received for a periodof time, clearing the recorded candidate fingerprint image from thedatabase.
 8. The fingerprint recognition method of claim 1, furthercomprising: if the signal quantity of the pixel array is insufficient,sensing other fingerprint images corresponding to the finger of the userthrough the fingerprint sensor disposed on the touch display.
 9. Thefingerprint recognition method of claim 8, wherein the step ofdetermining whether the signal quantity of the pixel array is sufficientcomprises: calculating and obtaining a fitting curve according to thegeometric center points of the fingerprint images, and calculating alength of the fitting curve; calculating and obtaining an extendedfitting curve extended from an end point of the fitting curve to an edgeof the fingerprint sensor, and calculating a length of the extendedfitting curve; if the length of the fitting curve is less than thelength of the extended fitting curve, determining that the signalquantity of the pixel array is insufficient; if the length of thefitting curve is not less than the length of the extended fitting curve,determining whether a new pixel point is present by searching backwardfrom the end point of the fitting curve along the fitting curveaccording to the length of the extended fitting curve; if the new pixelpoint is present, determining that the signal quantity of the pixelarray is insufficient; and if the new pixel point is absent, determiningthat the signal quantity of the pixel array is sufficient.
 10. Thefingerprint recognition method of claim 1, wherein the plurality ofsensing units disposed on a once-stretchable substrate having a straindetector, and the method further comprises, before the step of detectingthe touch signal corresponding to the user on the touch display,calculating a stretch rate near the strain detector; estimating astretch of each place on the once-stretchable substrate; estimatingdistances between the plurality of sensing units; and calculating aposition of at least one deformed pixel needed to be complement with asignal in the pixel array, wherein the other pixels include the at leastone deformed pixel.
 11. An electronic interactive apparatus, comprising:a processor; a touch display, coupled to the processor, and configuredto detect a touch signal corresponding to a user; a fingerprint sensor,coupled to the processor, and configured to sense a finger of the userto obtain a plurality of fingerprint images, wherein the fingerprintsensor has a plurality of sensing units and the finger of the user moveson the sensing units; and a storage device, coupled to the processor,wherein the fingerprint sensor respectively calculates geometric centerpoints corresponding to the fingerprint images, and calculates positionsand offsets of the fingerprint images according to the geometric centerpoints corresponding to the fingerprint images, wherein the fingerprintsensor is further configured to determine whether a signal quantity ofthe pixel array is sufficient, if the signal quantity of the pixel arraysufficient, the fingerprint sensor fills signals in the fingerprintimages into a part of pixels in a pixel array according to the positionsand the offsets of the fingerprint images, and obtains signals of otherpixels in the pixel array by inputting the signals filled in the part ofpixels in the pixel array into an artificial intelligence engine,wherein the fingerprint sensor generates a candidate fingerprint imageaccording to the pixel array, wherein the processor recognizes the useraccording to the candidate fingerprint image.
 12. The electronicinteractive apparatus of claim 11, wherein a trajectory of the finger ofthe user moving on the sensing units is a closed line segment or anunclosed line segment.
 13. The electronic interactive apparatus of claim11, wherein the fingerprint sensor recognizes pixel points having thesignals in each of the fingerprint images, and calculates the geometriccenter points of the fingerprint images according to the pixel pointshaving the signals in each of the fingerprint images.
 14. The electronicinteractive apparatus of claim 11, wherein the fingerprint sensorrecognizes pixel points having the signals in each of the fingerprintimages, and calculates the geometric center points of the fingerprintimages according to a contour of the pixel points having the signals ineach of the fingerprint images.
 15. The electronic interactive apparatusof claim 11, wherein the storage device stores a database, wherein theprocessor stores the candidate fingerprint image and a timestampcorresponding to the candidate fingerprint image in the database. 16.The electronic interactive apparatus of claim 15, wherein the touchdisplay detects another touch signals, wherein the fingerprint sensorsenses a plurality of second fingerprint images, respectively calculatesgeometric center points corresponding to the second fingerprint images,and calculates positions and offsets of the second fingerprint imagesaccording to the geometric center points corresponding to the secondfingerprint images, wherein the fingerprint sensor fills signals in thesecond fingerprint images into a part of pixels in a second pixel arrayaccording to the positions and the offsets of the second fingerprintimages, and obtains signals of other pixels in the second pixel array byinputting the signals filled in the part of pixels in the second pixelarray into the artificial intelligence engine, wherein the fingerprintsensor generates a second candidate fingerprint image according to thesecond pixel array, wherein the processor compares whether the secondcandidate fingerprint image is identical to the candidate fingerprintimage stored by the database, and if the second candidate fingerprintimage is not identical to the candidate fingerprint image, the processorstops to respond to the another touch signal.
 17. The electronicinteractive apparatus of claim 16, wherein when no other touch signalcorresponding to the user is received by the touch display for a periodof time, the processor clears the recorded candidate fingerprint imagefrom the database.
 18. The electronic interactive apparatus of claim 11,wherein if the signal quantity of the pixel array is insufficient, thefingerprint sensor senses other fingerprint images corresponding to thefinger of the user.
 19. The electronic interactive apparatus of claim18, wherein the fingerprint sensor is further configured to calculateand obtain a fitting curve according to the geometric center points ofthe fingerprint images, and calculate a length of the fitting curve, thefingerprint sensor is further configured to calculate and obtain anextended fitting curve extended from an end point of the fitting curveto an edge of the fingerprint sensor, and calculate a length of theextended fitting curve; if the length of the fitting curve is less thanthe length of the extended fitting curve, the fingerprint sensordetermines that the signal quantity of the pixel array is insufficient,if the length of the fitting curve is not less than the length of theextended fitting curve, the fingerprint sensor determines whether a newpixel point is present by searching backward from the end point of thefitting curve along the fitting curve according to the length of theextended fitting curve, if the new pixel point is present, thefingerprint sensor determines that the signal quantity of the pixelarray is insufficient, and if the new pixel point is absent, thefingerprint sensor determines that the signal quantity of the pixelarray is sufficient.
 20. The electronic interactive apparatus of claim11, further comprising: a strain detector, coupled to the processor,wherein the plurality of sensing units and the strain detector disposedon a once-stretchable substrate, wherein the strain detector isconfigured to measure a strain amount of the once-stretchable substrate,wherein the processor, based on the strain amount of theonce-stretchable substrate, calculates a stretch rate near the straindetector, estimates a stretch of each place on the once-stretchablesubstrate, estimates distances between the plurality of sensing units,and calculates a position of at least one deformed pixel needed to becomplemented with a signal in the pixel array, wherein the other pixelsinclude the at least one deformed pixel.